Anomaly Detection in Infrequently Occurred Patterns

Tuesday, March 14, 2017 - 10:55am11:20am

Dong Wang, Baidu Inc.

Abstract: 

Anomaly detection is one of the most important works of SREs. The usual way is to find some frequently occurred traffic patterns, and regards them as the normal value scopes. Any values beyond the scope will be regarded as the anomaly. However in some special dates, especially in some holidays, the traffics show the significantly different patterns. The commonly used alerting strategy usually does not work well. In this talk, we will introduce our approaches used to deal with such issues. Our scenarios are actually more complicated in that, in China, the holidays do not have the fixed calendar dates, and different holidays have absolutely different traffic patterns. However the practical deployment of the methods in this talk shows the pretty satisfying results in terms of alarming precision and recall.

Dong Wang, Baidu Inc.

Dong Wang is a principal architect at Baidu, the largest search engine in China, and has led Baidu’s SRE team to work on some challenging projects, such as automatic anomaly detection and issue fixing in large scale Internet sites. He is also interested in user experience improvement in the mobile Internet services. Prior to Baidu, he worked at Bell Labs and Google for more than 15 years in total.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

BibTeX
@conference {201821,
author = {Dong Wang},
title = {Anomaly Detection in Infrequently Occurred Patterns},
year = {2017},
address = {San Francisco, CA},
publisher = {{USENIX} Association},
month = mar,
}

Presentation Video

Download Video

Presentation Audio